Browsing by Author "Leung, Alexander A."
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- ItemOpen Access20-year trends in multimorbidity by race/ethnicity among hospitalized patient populations in the United States(2023-07-24) Mohamud, Mursal A.; Campbell, David J.; Wick, James; Leung, Alexander A.; Fabreau, Gabriel E.; Tonelli, Marcello; Ronksley, Paul E.Abstract Background The challenges presented by multimorbidity continue to rise in the United States. Little is known about how the relative contribution of individual chronic conditions to multimorbidity has changed over time, and how this varies by race/ethnicity. The objective of this study was to describe trends in multimorbidity by race/ethnicity, as well as to determine the differential contribution of individual chronic conditions to multimorbidity in hospitalized populations over a 20-year period within the United States. Methods This is a serial cross-sectional study using the Nationwide Inpatient Sample (NIS) from 1993 to 2012. We identified all hospitalized patients aged ≥ 18 years old with available data on race/ethnicity. Multimorbidity was defined as the presence of 3 or more conditions based on the Elixhauser comorbidity index. The relative change in the proportion of hospitalized patients with multimorbidity, overall and by race/ethnicity (Black, White, Hispanic, Asian/Pacific Islander, Native American) were tabulated and presented graphically. Population attributable fractions were estimated from modified Poisson regression models adjusted for sex, age, and insurance type. These fractions were used to describe the relative contribution of individual chronic conditions to multimorbidity over time and across racial/ethnic groups. Results There were 123,613,970 hospitalizations captured within the NIS between 1993 and 2012. The prevalence of multimorbidity increased in all race/ethnic groups over the 20-year period, most notably among White, Black, and Native American populations (+ 29.4%, + 29.7%, and + 32.0%, respectively). In both 1993 and 2012, Black hospitalized patients had a higher prevalence of multimorbidity (25.1% and 54.8%, respectively) compared to all other race/ethnic groups. Native American populations exhibited the largest overall increase in multimorbidity (+ 32.0%). Furthermore, the contribution of metabolic diseases to multimorbidity increased, particularly among Hispanic patients who had the highest population attributable fraction values for diabetes without complications (15.0%), diabetes with complications (5.1%), and obesity (5.8%). Conclusions From 1993 to 2012, the secular increases in the prevalence of multimorbidity as well as changes in the differential contribution of individual chronic conditions has varied substantially by race/ethnicity. These findings further elucidate the racial/ethnic gaps prevalent in multimorbidity within the United States. Prior presentations Preliminary finding of this study were presented at the Society of General Internal Medicine (SGIM) Annual Conference, Washington, DC, April 21, 2017.
- ItemOpen AccessCongenital Bands with Intestinal Malrotation after Propylthiouracil Exposure in Early Pregnancy(2015-11-18) Leung, Alexander A.; Yamamoto, Jennifer; Luca, Paola; Beaudry, Paul; McKeen, JulieExposure to propylthiouracil in early pregnancy may be associated with an increased risk of birth defects. But the spectrum of associated congenital anomalies is not yet well defined. While preliminary reports suggest that most cases of propylthiouracil-associated birth defects are restricted to the preauricular and urinary systems, careful consideration should be given to other possible manifestations of teratogenicity. We propose that congenital bands may potentially represent a rare yet serious complication of propylthiouracil exposure in early pregnancy, possibly arising from an early mesenteric developmental anomaly. We report a case of a 17-day-old girl that presented with acute small bowel obstruction associated with intestinal malrotation arising from several anomalous congenital bands. Her mother was treated for Graves’ disease during pregnancy with first trimester exposure to propylthiouracil but remained clinically and biochemically euthyroid at conception and throughout the duration of pregnancy. This case suggests that the use of propylthiouracil in early pregnancy may be associated with congenital bands and intestinal malrotation. More reports are needed to further support this association.
- ItemOpen AccessPersonalized prediction of incident hospitalization for cardiovascular disease in patients with hypertension using machine learning(2022-12-17) Feng, Yuanchao; Leung, Alexander A.; Lu, Xuewen; Liang, Zhiying; Quan, Hude; Walker, Robin L.Abstract Background Prognostic information for patients with hypertension is largely based on population averages. The purpose of this study was to compare the performance of four machine learning approaches for personalized prediction of incident hospitalization for cardiovascular disease among newly diagnosed hypertensive patients. Methods Using province-wide linked administrative health data in Alberta, we analyzed a cohort of 259,873 newly-diagnosed hypertensive patients from 2009 to 2015 who collectively had 11,863 incident hospitalizations for heart failure, myocardial infarction, and stroke. Linear multi-task logistic regression, neural multi-task logistic regression, random survival forest and Cox proportional hazard models were used to determine the number of event-free survivors at each time-point and to construct individual event-free survival probability curves. The predictive performance was evaluated by root mean squared error, mean absolute error, concordance index, and the Brier score. Results The random survival forest model has the lowest root mean squared error value at 33.94 and lowest mean absolute error value at 28.37. Machine learning methods provide similar discrimination and calibration in the personalized survival prediction of hospitalizations for cardiovascular events in patients with hypertension. Neural multi-task logistic regression model has the highest concordance index at 0.8149 and lowest Brier score at 0.0242 for the personalized survival prediction. Conclusions This is the first personalized survival prediction for cardiovascular diseases among hypertensive patients using administrative data. The four models tested in this analysis exhibited a similar discrimination and calibration ability in predicting personalized survival prediction of hypertension patients.